---
language:
- en
- de
- es
- fr
- ja
- ko
- zh
- it
- pt
license: other
license_name: ltx-2-community-license-agreement
license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE.md
pipeline_tag: image-to-video
tags:
- gguf
- quantized
- image-to-video
- text-to-video
- video-to-video
- audio-to-video
- ltx-video
- lightricks
- ltx-2.5
base_model: Lightricks/LTX-2.5
---

# LTX-2.5 Distilled GGUF

This repository provides quantized GGUF formats of the distilled transformer from [Lightricks/LTX-2.5](https://huggingface.co/Lightricks/LTX-2.5). These weights are highly optimized for local execution, allowing you to run high-fidelity video and audio generation workflows on hardware with memory constraints while retaining the core visual fidelity of the original base model.

## Available Quantizations

| File | Size | Description |
|---|---|---|
| **LTX-2.5-Distilled-Q3_K_M.gguf** | 11.5 GB | Smallest footprint with the highest quantization loss. Best for strict memory limits. |
| **LTX-2.5-Distilled-Q4_K_S.gguf** | 13.9 GB | Slightly smaller than Q4_K_M, balancing speed and limited VRAM/RAM. |
| **LTX-2.5-Distilled-Q4_K_M.gguf** | 15.1 GB | Recommended baseline. Good balance of visual fidelity, motion consistency, and memory footprint. |
| **LTX-2.5-Distilled-Q5_K_M.gguf** | 16.8 GB | Higher precision, retaining strong prompt adherence with minimal degradation. |
| **LTX-2.5-Distilled-Q6_K.gguf** | 18.7 GB | Near-unquantized visual quality, very low quantization loss. |
| **LTX-2.5-Distilled-Q8_0.gguf** | 23.6 GB | Largest quantized footprint, nearly indistinguishable from the original bf16 weights. |

## About the Original Model

**LTX-2.5** is an open-world model built for local execution and fine-tuning. It specializes in generating synchronized, high-fidelity video and audio from text, image, and video inputs.

### Key Features of LTX-2.5
* **Native Multishot Generation:** Generate connected scenes in a single pass holding character identity, environment, lighting, voice, and visual style across cuts.
* **Diffusion Fidelity Rendering:** The model dynamically allocates compute based on scene complexity, rendering flawless detail where needed.
* **Distilled Efficiency:** These GGUF checkpoints are derived from the distilled model, capturing much of the full 22B model's capabilities in a significantly faster, smaller package.

## Usage Requirements

Ensure your inference engine (such as `llama.cpp` or compatible ComfyUI GGUF loader nodes) supports the LTX-2.5 DiT architecture. Depending on the quantization tier, appropriate system RAM or GPU VRAM size must be allocated to accommodate the file sizes listed above.

## License & Limitations

These weights fall under the original [LTX-2.x Community License](https://github.com/Lightricks/LTX-2/blob/main/LICENSE.md). Commercial and production use is permitted at no cost for entities under $10M annual revenue. 

* This model is not intended or able to provide factual information.
* Prompt following is heavily influenced by prompting style.
* The model may fail to generate videos that match the prompt perfectly or may generate artifacts in highly complex scenes.

For full architectural details, official multishot prompting guides, and citation information, please refer to the [Original LTX-2.5 Model Card](https://huggingface.co/Lightricks/LTX-2.5).